Predictive skills – Are you a Fox or Hedgehog?

It’s unlikely that you have ever wondered whether you are more like Fox or a Hedgehog. Important scholars stretching back to the Grecians have, however, used this animal analogy to characterise important traits that illustrate the way we think and impact our ability to successfully predict. One man’s crusade to measure predictive ability and relate to the Fox-Hedgehog dichotomy led him to insights that gamblers should find eye-opening.


Honing your betting skills is essentially the pursuit of more accurate predictions. This is a challenge that transcends gambling, and has huge implications for spheres such as finance, civic planning and politics, and essentially relates to how we think.

The Greek poet Archilochus suggested that ‘foxes know many things and the hedgehog one big thing’. Several important thinkers since have expanded on this concept to suggest that the way people think can generally be characterised as being Fox or Hedgehog like.

“Who the hell wants to hear actors talk?” — H. M. Warner, Warner Brothers, 1927.

One of the great difficulties in measuring predictive ability is that those same fields where the implications of the accuracy of predictions are so profound – think poor Intelligence and the Iraq war – accountability is rare, or very difficult to pin down. One man however, has tracked predictions for over two decades, exploring what constitutes good judgement and utilising the Hedgehog vs. Fox distinction. His insights make fascinating and hugely pertinent reading for gamblers.

Philip Tetlock spent 20 years recording the predictions of government officials, professors, journalists and politicians, and discovered that from over 28,000 predictions they were only slightly more accurate than chance. His work and approach are summarised in his 2005 book: ‘Expert Political Judgement? How good is it? How can we know?’

Tetlock developed an array of calibrations and adjustments in order to be fair to those making predictions, and his results were shocking, effectively suggesting that (as a whole) experts were only marginally better than chance.

Rather than writing off all forecasters, Tetlock was able to distinguish characteristics that identify someone as being better suited to making more accurate predictions, and these are equally valuable whether you are trying to make a complex policy decision or trying to consistently predict sporting outcomes.

Tetlock’s approach was to avoid looking at specific successes: how many times have you seen tipsters and talking-heads trying to live off the glory of rare headline grabbing predictions? Instead, he gave more credit to consistent predictive success over time and in differing contexts.

Success wasn’t reduced to a yes or no assessment, because prediction is as much about correctly predicting future events as it is the speed with which you recognise you have got things wrong and subsequently adjust your belief.

It does Tetlock a disservice to summarise his work in a few words, but for the purposes of aspiring gamblers the key take away is to focus on thinking the right way.

Nate Silver provided a useful summary table that outlines the important character traits that Tetlock’s work discovered:

Fox-like characteristics Hedgehog-like characteristics
Multidisciplinary – Incorporates ideas from a range of disciplines Specialised – Often dedicated themselves to one or two big problems & are sceptical of outsiders
Adaptable – Try several approaches in parallel, or find a new one if things aren’t working Unshakable – New data is used to refine an original model
Self-critical – Willing to accept mistakes and adapt or even replace a model based on new data Stubborn – Mistakes are blamed on poor luck
Tolerant of complexity – Accept the world is complex, and that certain things cannot be reduced to a null hypothesis Order seeking – Once patterns are detected, assume relationships are relatively uniform
Cautious – Predictions are probabilistic, and qualified Confident – Rarely change or hedge their position
Empirical – Observable data is always preferred over theory or anecdote Ideological – Approach to predictive problems fits within a similar view of the wider world

The Fox-like approach is an agile one, incorporating changing circumstances to refine and adjust your predictions. Anyone who applies Bayesian analysis will quickly recognise the connection.

Bayesian theorem uses an iterative process of assessing what you know about the probability of a future event, then tests the impact of new evidence as it becomes available. Bayes was an 18th century English Presbyterian Minister, but almost certainly a fox.

Of course a Fox-like approach doesn’t imply infallibility. Getting things wrong is inevitable, the key thing is to use an approach that maximises your chances of getting things right.

Which animal characterises your way of thinking about uncertainty? It may help you improve your betting.